In recent years, research concerning the reconstruction of a measured object as an image by utilizing computer graphics technology, by using three dimensional measurement data (range image) obtained from highly accurate laser range sensors has been carried out.
In normal three dimensional shape measuring, laser range sensors are installed on the ground, and scanning is performed from multiple directions so that the object to be measured can be measured exhaustively. However, in cases where the object to be measured and its surrounding environment is, for example, a large building, the measurement range of the laser range sensor will be limited to the surface regions that can be observed from the sensor, so that points that are beyond the measurable range of the sensor, or points that are occluded, will exist. For example, unmeasured region 15 and the like in FIG. 1, indicated by slanted lines, corresponds to such points, so that measuring from the ground only will be insufficient.
In the conventional art, in order to overcome this problem, measuring is generally done by building a scaffold that is higher than the portion that cannot be observed due to being blocked, and installing a laser range sensor on top of the scaffold. Whereby, it becomes possible to perform the measurement of the aforementioned unmeasured region 15 in FIG. 1, but said method presupposes that there are no problems in the state of the ground on which the scaffold is to be built, and a scaffold can be safely constructed. Further, as the shape of the observed object becomes more complex, measurement from many different viewpoints becomes necessary, and reconstructing a scaffold and installing a range sensor each time requires a large amount of labor and cost.    Non-Patent Document 1: K. Nishino and K. Ikeuchi: Robust simultaneous registration of multiple range images. Proceedings of the 5th Asian Conference on Computer Vision, Vol. 2, pp. 455-461, (2002)    Non-Patent Document 2: T. Masuda: 3d shape restoration and comparison through simultaneous registration. Master's thesis, Graduate School of Information Science and Technology, University of Tokyo, (2003)    Non-Patent Document 3: Mark D. Wheeler: Automatic Modeling and Localization for Object Recognition. PhD thesis, School of Computer Science, Carnegie Mellon University, (1996)    Non-Patent Document 4: E. Polak: Computational Methods in Optimization. New York: Academic Press, (1971)    Non-Patent Document 5: David A. H. Jacobs: The States of the Art in Numerical Analysis. London; Academic Press, (1977)    Non-Patent Document 6: J. Stoer and R. Bulirsch: Introduction to Numerical Analysis. New York; Springer-Verlag, (1980)